Deep Vision

Course Information

  • Lecturer Dr. Frank Lenzen , Prof. Björn Ommer
  • Lecture extend (2+2 SWS)
  • Time & date:
    • Lecture Mo 14:15-15:45
    • Exercise: Mo 16:00-17:30,
  • Room : HCI (Speyerer Straße 6)
    • Lecture: large seminar room 2.floor room H2.22
    • Exercise : small seminar room 3rd floor 3. OG
  • Language: English


The lecture covers two topics:

Topic 1: Deep Learning, in particular Deep Convolutional Neuronal Networks (CNNs). As basics for Deep Neural Networks we will discuss convolutions, filters , Fourier analysis, wavelets overcomplete bases, learning, optimization, before going in to detail on neural networks.

Topic 2: Multiview geometry and 3D scene estimation. Subtopics are camera models and camera geometry, stereo, structure from motion, optical flow, depth estimation


  • standard certificates ('Schein') after passing exercises and oral exam
  • certificate for attendance ('Sitzschein'): regular attendance required (absence in not more than 2 lectures )
  • Exercises partly build on MATLAB. Alternatively the students may use octave oder NumPy.


Additional material is posted in moodle.

Since currently not all students have moodle accounts, <a href=""> this </a> is an alternative link:

(same password as for moodle).